Skip to main content
JAMA Network logoLink to JAMA Network
. 2023 Jun 20;177(8):857–859. doi: 10.1001/jamapediatrics.2023.1738

Trends, Distribution, and Impact of Pediatric Messages in a Large Health System From 2019 to 2021

Maria C Tang 1,, Kathryn A Martinez 2, Michael B Rothberg 2, Kimberly Giuliano 1, Elizabeth R Pfoh 2
PMCID: PMC10282955  PMID: 37338865

Abstract

This cohort study assesses changes in the volume of medical advice messages between 2019 and 2021, variation among pediatricians, and the association of volume with time spent working on the electronic health record outside clinical hours.


Physicians spend a quarter of their day responding to messages.1 While messaging uptake is heterogeneous across practice types,2 how volume varies across pediatricians is understudied. Since responding to messages after hours is associated with burnout,3 understanding variation is important. This cohort study assessed changes in the volume of medical advice messages between 2019 and 2021, variation across pediatricians, and the association between volume and time spent working on the electronic health record (EHR) outside clinical hours.

Methods

We included full-time pediatricians (≥0.8 full-time equivalent [FTE]) and pediatric patients who visited Cleveland Clinic between January 2019 and December 2021. Cleveland Clinic’s institutional review board approved this study; informed consent was waived due to minimal risk. We followed the STROBE reporting guideline. We obtained pediatricians’ years of service and sex and patients’ age, sex, race, and insurance status. We identified pediatricians’ total number of in-person visits, patient-initiated medical advice messages, and telephone calls each quarter through EHR data, including time spent on the EHR outside clinical hours. To account for the COVID-19 pandemic and reduce seasonality effects, we compared changes in use between quarters 4 (October to December 2019) and 12 (October to December 2021). We used group-based modeling, a method for analyzing trajectories,4 to categorize pediatricians based on their message volume over time. After stratifying by group status, we used regression models controlling for pediatrician and patient characteristics to describe changes in message, visit, and telephone call volume between quarters 4 and 12. We used mixed-effects linear regression to evaluate the association between group status and time spent on the EHR outside clinical hours, accounting for clustering by time, visit volume, and patient and pediatrician characteristics and generated estimated means. We assessed changes in time spent on the EHR outside clinical hours within each group by comparing quarters 4 and 12 using a regression model with the same fixed variables. Data were analyzed using Stata, version 16.0. Two-sided P < .01 was considered significant.

Results

We included 72 pediatricians (54 [76%] female; 18 [24%] male) and 115 273 patients (57 078 [50%] female; 58 167 [50%] male; mean [SD] age, 7.3 [6.0] years) with 450 083 visits. Mean (SD) number of service years among pediatricians was 13 (10). Most patients (75%) had private insurance. Per 100 visits, medical advice messages increased from 15 in 2019 to 44 in 2021.

We categorized pediatricians into 3 groups: 45 (63%), low volume (105 messages per quarter); 21 (29%), medium volume (237); and 6 (8%), high volume (371) (Figure 1). Medical advice messages increased between quarters 4 and 12; the greatest increase occurred in the high-volume group (β = 337) followed by the medium-volume (β = 241) and the low-volume (β = 118) groups. FTE did not differ between pediatricians in the low and high groups. Per pediatrician, visit volume decreased from 643 in quarter 4 to 549 in quarter 12 (P = .007), while messages increased from 112 in quarter 4 to 278 in quarter 12 (P < .001) (Figure 2). Compared with low-volume pediatricians (19; 95% CI, 17-21 hours per quarter), medium-volume (27; 95% CI, 24-29 hours per quarter) and high-volume (26; 95% CI, 23-30 hours per quarter) pediatricians spent 7.5 additional hours per quarter on the EHR outside clinical hours (P < .001); within each group, there was no significant difference over time.

Figure 1. Mean Number of Medical Advice Messages and Visits per Quarter Between 2019 and 2021 by Group.

Figure 1.

Figure 2. Adjusted Number of Visits, Messages, and Telephone Calls in the Fourth and Twelfth Quarter by Group.

Figure 2.

Discussion

In this study, the high-volume group received 3 times the medical advice messages as the low-volume group; mean message volume was similar to another study.5 Within groups, time on the EHR outside clinical hours did not increase, perhaps because visits decreased. As office visits rebound, health systems may need to support pediatricians’ ability to handle their workload by charging for messages,5 dedicating time to responding, offering scribes,6 or adjusting panel sizes. The small sample and inability to differentiate how time was spent on the EHR are limitations. Health systems could use message burden to identify who needs support.

Supplement.

Data Sharing Statement

References

  • 1.Arndt BG, Beasley JW, Watkinson MD, et al. Tethered to the EHR: primary care physician workload assessment using EHR event log data and time-motion observations. Ann Fam Med. 2017;15(5):419-426. doi: 10.1370/afm.2121 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Heisey-Grove D, Rathert C, McClelland LE, Jackson K, DeShazo JP. Patient and clinician characteristics associated with secure message content: retrospective cohort study. J Med Internet Res. 2021;23(8):e26650. doi: 10.2196/26650 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Tran B, Lenhart A, Ross R, Dorr DA. Burnout and EHR use among academic primary care physicians with varied clinical workloads. AMIA Jt Summits Transl Sci Proc. 2019;2019:136-144. [PMC free article] [PubMed] [Google Scholar]
  • 4.Nagin DS. Group-based trajectory modeling: an overview. Ann Nutr Metab. 2014;65(2-3):205-210. doi: 10.1159/000360229 [DOI] [PubMed] [Google Scholar]
  • 5.Holmgren AJ, Byron ME, Grouse CK, Adler-Milstein J. Association between billing patient portal messages as e-visits and patient messaging volume. JAMA. 2023;329(4):339-342. doi: 10.1001/jama.2022.24710 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Pfoh ER, Hong S, Baranek L, et al. Reduced cognitive burden and increased focus: a mixed-methods study exploring how implementing scribes impacted physicians. Med Care. 2022;60(4):316-320. doi: 10.1097/MLR.0000000000001688 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

Data Sharing Statement


Articles from JAMA Pediatrics are provided here courtesy of American Medical Association

RESOURCES